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  1. Observational Research

  2. Observational Research • Naturalistic Observation: • Unobtrusive observation (avoid the Hawthorne Effect) • Habituation • Indirect measures • Count the results of behavior, use a survey • Disadvantages: time & money • Advantages: ecological validity

  3. Observational methods • EEthnography: researcher is immersed in the behavioral or social system being studied. Often used by anthropologists (skip pages 239-242) • Decide whether to be a participant or nonparticipant and overtly or covertly • Reactivity might be a problem if overt and ethical issues might surface if using covert method is used • Issues related to gaining access to a setting or group might present

  4. Observational Methods • Case histories require that you study a single or just a few cases • Case studies are particularly useful when the goals is behavioral change or when organizations are studied (e.g., learning/education/ and industrial/organizational settings)

  5. Observational Methods • Archival research involves studying existing records such as historical accounts, police records, published articles, or media • Requires a specific and refined hypothesis • Might consider how you will gain access to the data, the completeness of the record (do you need more than one source)

  6. Observational Methods • Content analysis: involves analyzing verbal written or spoken record for the occurrence of specific categories of events, items, or behavior. • Some overlap with archival research; some people define content analysis as pertaining specifically to language while others have a broader definition. • Might include conversations, books, movies, blogs, etc. • Successful content analyses require that researchers be objective and systematic, and have clear operational definition and/or coding schemes. • Consider issues related to sampling (avoid a biased sample) and observer bias (more than one coder)

  7. Behavioral Categories & Coding Schemas • Behavioral categories operationally define what behaviors are coded during the observation period • Clearly defined hypotheses • To develop categories you could make preliminary observations, conduct a lit review, or be very specific about your research goals and hypotheses

  8. Quantifying Behaviors • Frequency method: record the number of times a behavior occurs • Duration method: record how long the behavior lasts. • Interval method: divide the observation period into time intervals, record the number of times the behavior occurs within each time interval (e.g., verbal exclusion during 2 minute time periods)

  9. Recording single events vs. behavioral sequences • Behavioral sequence can be thought of • ABC’s of the behavior: antecedent, behavior, consequence • Antecedent only or consequence only

  10. Consider sampling or recording complex behaviors • Time sampling • Individual sampling • Event sampling: observe only one behavior • Record behaviors code later by watching video repeatedly

  11. Reliability • Interrater reliability: involves using multiple coders • Ensures that observers are accurate • Allows for replication • Allows coders to detect and correct any discrepancies

  12. Methods of determining reliability • Percent agreement ((total # agreement/total # observation) x 100)); >70% is acceptable • Cohen’s Kappa κ = Po – Pc/1– Pc • Used for categorical or dichotomous data • where P o = observed proportion of actual agreement, and Pc = proportion of expected agreement • Pearson’s r • can be used with continuous data but it might produce a significant correlation if disagreements are numerous (as long as the magnitudes increase or decrease in a similar fashion) • Intraclass correlation coefficient (ICC) • (rI) should be used for continuous data. This method uses an ANOVA approach (means squares within and between subjects

  13. Sources of bias • Observer bias: when being aware of the hypothesis influences coding. Can use blind observers • Observers interpret rather than record behavior

  14. Chi square • A non parametric test • chi-square & fisher’s exact test is distribution free and relies only on frequencies • tests can only be used under certain circumstances • chi-squares: dichotomous or categorical data • fisher’s exact: 2 by 2 table or two dichotomous variables.

  15. Chi-square • To calculate χ2 determine the frequency of each cell if no differences existed (frequency expected, (ƒe) and then compare this to the actual or observed frequencies (ƒo). • The greater the difference between expected and observed frequencies the more likely it is that differences exist. • χ2 = ∑ (ƒo – ƒe)2/ ƒe • Compare χ2 observed to χ2 critical in the χ2 sampling distribution

  16. Chi-square • To report your findings: • χ2(df, N = #) = statistic value, p-value • χ2(1,N = 90) = 0.89, p = .35 • Where df = (r-1) x (c-1)